This repository stores codes to (1) select the optimal (i.e. best estimator in a MSE sense) limb-darkening law for a given transiting exoplanet lightcurve and (2) calculate the limb-darkening induced biases on various exoplanet parameters.
The details of the codes are explained in Espinoza & Jordán (2016, MNRAS, in press.; arXiv e-print: http://arxiv.org/abs/1601.05485). Source code of the paper (including generation of all figures): https://github.com/nespinoza/lds_which_law_2_use.
This code makes use of three important libraries:
+ The Bad-Ass Transit Model cAlculatioN (batman) package: http://astro.uchicago.edu/~kreidberg/batman/
+ The latest version of the lmfit fitter (https://lmfit.github.io/lmfit-py/)
+ The LDC3.py code wrote by David Kipping (https://github.com/davidkipping/LDC3)
This last code might be updated with time, but I have copied here the October 29th, 2015 version of it for reference: be sure to use the latest version of D. Kipping's code!
The usage of the code is simple, depending on what you want to do:
-
Do you want to know which law to use in a given application?
You are looking for the
which_law_should_i_use.pycode. Simply modify the parameters inside the code and let the simulations run. At the end, the code will print out the Bias/Precision values for each law so you can select the optimal one for your application. -
You want to perform bias simulations for several transit parameters?
Then you want to use the
run_ld_exosim.pycode. In the code just define the parameters you woud like to explore and run it. The results will be saved in a folder named "results" for your simulation, where the biases for both fixed and free parameters will be stored.
Both codes make use of limb-darkening tables stored in the ld_tables folder,
which already has a table containing all the limb-darkening coefficients using
the ATLAS models and the Kepler bandpass. To generate your own table, you can use
our code at https://github.com/nespinoza/limb-darkening and put the result inside.